GEMR:KG – Global Emerging Market Risk Knowledge Graph
Published in 19th IADIS International Conference on Information Systems and 24th International Conference on e-Society (IS/ES), 2026, 2026
A prevailing perception of high risk in emerging markets, often driven by incomplete and fragmented data, leads to capital misallocation and constrains investment. While datasets such as the World Bank’s Global Economic Monitor (GEM) and the Global Emerging Markets (GEMR) Risk Database provide extensive macroeconomic and credit risk information, they exist in silos, limiting holistic analysis. This paper introduces the Global Emerging Markets Risk Knowledge Graph (GEMR: KG), a system that integrates these sources into a unified, semantically rich framework. GEMR: KG models entities including countries, loans, economic indicators, and crisis events, along with their interrelationships, enabling multi-relational queries such as tracing the geographic contagion of defaults or identifying leading macroeconomic indicators of credit stress. The system features a dual-interface querying capability, supporting formal SPARQL for quantitative analysts.
Recommended citation: A. G. Ravishankar. "GEMR:KG – Global Emerging Market Risk Knowledge Graph." 19th IADIS International Conference on Information Systems and 24th International Conference on e-Society (IS/ES), 2026, pp. 143–150.
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